code: def _aspect_preserving_resize(image, resize_min):
      """Resize images preserving the original aspect ratio.
  
      Args:
        image: A 3-D image `Tensor`.
        resize_min: A python integer or scalar `Tensor` indicating the size of
          the smallest side after resize.
  
      Returns:
        resized_image: A 3-D tensor containing the resized image.
      """
      shape = tf.shape(input=image)
      height, width = shape[0], shape[1]
  
      new_height, new_width = _smallest_size_at_least(
          height, width, resize_min
      )
  
      return _resize_image(image, new_height, new_width)
  
file_path: autodist/examples/benchmark/utils/imagenet_preprocessing.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  from absl import logging
  import tensorflow
label_desc: Use image node_id 10 for calling a global function with example usage: _aspect_preserving_resize(image, resize_min) and returns: _resize_image